Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Palladium-catalyzed olefination and arylation of 2-substituted 1,2,3-triazole N-oxides.

Organic letters·2013
Same author

One-stop hybrid coronary revascularization versus coronary artery bypass grafting and percutaneous coronary intervention for the treatment of multivessel coronary artery disease: 3-year follow-up results from a single institution.

Journal of the American College of Cardiology·2013
Same author

Relative contributions of the thalamus and the paraventricular nucleus of the hypothalamus to the cardiac sympathetic afferent reflex.

American journal of physiology. Regulatory, integrative and comparative physiology·2013
Same author

Initial light soaking treatment enables hole transport material to outperform spiro-OMeTAD in solid-state dye-sensitized solar cells.

Journal of the American Chemical Society·2013
Same author

The rice GERMINATION DEFECTIVE 1, encoding a B3 domain transcriptional repressor, regulates seed germination and seedling development by integrating GA and carbohydrate metabolism.

The Plant journal : for cell and molecular biology·2013
Same author

Salvage intensity modulated radiotherapy using endorectal balloon after radical prostatectomy: clinical outcomes.

International journal of urology : official journal of the Japanese Urological Association·2013

Related Experiment Video

Updated: Dec 6, 2025

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.2K

UENet: A Novel Generative Adversarial Network for Angiography Image Segmentation.

Xiaotong Shi, Tianming Du, Shuang Chen

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |October 6, 2020
    PubMed
    Summary

    This study introduces an adapted generative adversarial network (GAN) for improved coronary angiography vessel segmentation. The novel approach enhances feature extraction, effectively addressing segmentation discontinuity and improving accuracy for medical imaging analysis.

    More Related Videos

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
    04:48

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

    Published on: July 5, 2024

    675
    Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
    05:56

    Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

    Published on: April 14, 2023

    3.0K

    Related Experiment Videos

    Last Updated: Dec 6, 2025

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
    04:48

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

    Published on: November 30, 2022

    3.2K
    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
    04:48

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

    Published on: July 5, 2024

    675
    Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
    05:56

    Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

    Published on: April 14, 2023

    3.0K

    Area of Science:

    • Medical Imaging
    • Artificial Intelligence
    • Biomedical Engineering

    Background:

    • Convolutional neural networks (CNNs) are common for medical image segmentation.
    • Coronary angiography vessel segmentation is challenging due to poor opacification, overlapping segments, and tissue similarity.
    • Existing methods often yield sub-optimal segmentation performance.

    Purpose of the Study:

    • To propose an adapted generative adversarial network (GAN) for accurate semantic segmentation of coronary angiography images.
    • To overcome limitations in extracting fine coronary artery features for improved segmentation.
    • To enhance segmentation discontinuity and intra-class consistency.

    Main Methods:

    • An adapted U-net served as the generator within the GAN framework.
    • A novel 3-layer pyramid structure was implemented as the discriminator.
    • Multi-scale inputs were utilized during training to optimize objective functions for high-definition results.

    Main Results:

    • The proposed GAN effectively extracts fine coronary artery features.
    • The method successfully addresses segmentation discontinuity and intra-class inconsistencies.
    • Experimental results demonstrate improved segmentation accuracy compared to existing vessel segmentation techniques.

    Conclusions:

    • The adapted GAN provides a robust solution for coronary angiography vessel segmentation.
    • The novel architecture enhances the extraction of critical vascular structures.
    • This approach offers a significant improvement in medical image segmentation accuracy.